About

Runtime-Governed AI for Stable, Long-Horizon Systems

Public specification. Proprietary runtime. DOI-archived research corpus.

What is Sigma Stratum

Sigma Stratum is a runtime architecture framework for stable, long-horizon AI systems.

It defines the foundation behind the Sigma Runtime Standard (SRS), the SRIP public specification layer, and Sigma Runtime.

Sigma Stratum is not a model, an agent orchestrator, or a prompt framework. It is a runtime-governance layer for controlling how AI systems preserve context, memory, reasoning stability, provenance, action boundaries, and recursive continuity across extended interactions.

The core premise is simple:

AI capability is not determined only by model weights. It is also shaped by the governed runtime loop through which models remember, retrieve, verify, act, exchange, adapt, and stabilize over time.

Sigma Runtime Standard (SRS) and SRIP

The Sigma Runtime Standard (SRS) is a public specification framework for runtime-governed AI systems.

SRS and the Sigma Runtime Improvement Proposal (SRIP) registry define architectural surfaces for:

- canonical runtime loops

- drift detection and stabilization

- attractor state modeling

- symbolic density control

- long-term memory governance

- adaptive entropy regulation

- retrieval and memory integration

- relational identity stabilization

- controlled perturbation

- multi-agent exchange

- contradiction buffering

- autonomy negotiation

- external identity binding

- governance recursion and certification boundaries

The SRS/SRIP layer is vendor-agnostic and model-agnostic. It does not require modification of model weights. It defines how external runtime layers structure reasoning, memory, retrieval, validation, exchange, and governance around modern AI systems.

The public documentation corpus is archived on Zenodo with DOI-based citation metadata.

Sigma Runtime

Sigma Runtime is the proprietary operated implementation surface corresponding to the public SRS/SRIP specification layer.

It functions as an external runtime layer designed to:

- bound reasoning drift

- preserve contextual integrity across extended workflows

- govern memory and retrieval behavior

- enforce runtime-level constraints

- support auditability and traceability

- stabilize recursive interaction trajectories

- enable controlled multi-step and multi-agent operation

Sigma Runtime is designed for high-accountability environments where consistency, observability, and rule integrity must hold across long-horizon AI workflows.

It is compatible with modern large language models and does not require model fine-tuning. Stability is achieved through structured runtime governance rather than modification of base model weights.

Research Foundations

Sigma Stratum builds on a DOI-archived research lineage in recursive cognition, symbolic density, attractor architectures, neurosymbolic scaffolding, runtime continuity, and AI governance.

The research program investigates how long-horizon AI systems can remain coherent, adaptive, bounded, and non-capturable across recursive transformation.

This research informs the public SRS/SRIP specification surface and the proprietary Sigma Runtime implementation layer.

Public Specification and Product Boundary

Sigma Stratum separates four surfaces:

- public SRS/SRIP specification materials

- research-origin documentation and publications

- proprietary Sigma Runtime product assets

- marks, compatibility, certification, and commercial deployment governance

Public documentation does not imply certification, endorsement, official compatibility, permission to use protected Sigma marks, managed deployment rights, white-label rights, resale authorization, or access to proprietary runtime assets.

Independent implementation of public SRS/SRIP specification requirements is permitted under the applicable public specification terms. Sigma Runtime, official certification, compatibility badges, protected marks, and commercial runtime services are governed separately.

Vision

Sigma Stratum aims to define the runtime-governance layer for long-horizon AI systems.

The goal is to make advanced AI systems not only more capable, but more stable, auditable, provenance-aware, and deployable under bounded reasoning constraints.

In short:

Sigma Stratum defines the architecture.

SRS/SRIP defines the public specification surface.

Sigma Runtime operationalizes the runtime.